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A Pollution Sensitive Marxian Production Inventory Model with Deterioration Under Fuzzy System

This article deals with an economic production quantity (EPQ) model with deterioration under the effect of environmental pollution in fuzzy environment. First of all, we develop a pollution generation (PG) model with the help of existing initial pollution status of the environment, and then we use i...

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Detalles Bibliográficos
Autores principales: De, Sujit Kumar, Bhattacharya, Kousik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758230/
https://www.ncbi.nlm.nih.gov/pubmed/35043023
http://dx.doi.org/10.1007/s10957-021-01979-9
Descripción
Sumario:This article deals with an economic production quantity (EPQ) model with deterioration under the effect of environmental pollution in fuzzy environment. First of all, we develop a pollution generation (PG) model with the help of existing initial pollution status of the environment, and then we use it as an essential constraint in the proposed EPQ model. The model has also been studied in two different scenarios: (a) when unit selling price is given and (b) when unit selling price is associated with marginal profit respectively. However, in this article, the concept of manpower exploitation, law of surplus value and their impacts on profit function has been discussed. In fact, after the invention of Marxian production theory (1867), not a single article has been developed for studying inventory management problems/operations research using this theory. Thus, in this study, focussing Marxian principle we have developed a new production inventory model named Marxian economic production quantity (M-EPQ) model incorporating the extensions of the models developed by Harris (Mag Manag 10(2):135–136, 1913) and Taft (Iron Age 101:1410–1412, 1918) exclusively. Moreover, to deal with the non-random uncertainties of several cost components of production process we have utilized fuzzy system explicitly. A case study has been performed for numerical illustrations and we have developed a solution algorithm for numerical computations. Finally, sensitivity analysis and graphical illustrations are made to validate the new M-EPQ model followed by a conclusion.